Plot Survival vs Guan score


Risk prediction summary by quality of model
Summary statistics by subtype

true and false positive percentages
|
|
TPR
|
FPR
|
|
subtype
|
low
|
high/extreme
|
extreme
|
low
|
high/extreme
|
extreme
|
|
FGFR3
|
88.0
|
86.0
|
80.0
|
12.00
|
14.0
|
20.00
|
|
t(4;14)
|
87.5
|
85.7
|
90.9
|
12.50
|
14.3
|
9.09
|
|
del1p
|
97.0
|
36.0
|
29.0
|
3.00
|
64.0
|
71.00
|
|
amp1q
|
94.0
|
64.0
|
53.0
|
6.00
|
36.0
|
47.00
|
|
del13
|
98.0
|
46.0
|
54.0
|
2.00
|
54.0
|
46.00
|
|
agnostic
|
92.5
|
31.8
|
19.7
|
7.45
|
68.2
|
80.30
|
SYGNAL risk prediction for each subject was chosen based on the
quality of the subtypes each subject exhibited. If a subject exhibited
multiple subtypes then the average of the best quality models risk
prediction was used to classify the subject. If no subtypes were
exhibited then the “all” model was used. For example, if a subject
exhibited the t(4;14), amp1q, and del(1p) subtypes then the t(4;14)
subdtype risk prediction would be used for that subject.
|
subtype
|
AUC
|
quality
|
|
FGFR3
|
0.932
|
A
|
|
t(4;14)
|
0.918
|
A
|
|
del(13)
|
0.890
|
B
|
|
del(1p)
|
0.878
|
B
|
|
amp(1q)
|
0.843
|
B
|
|
agnostic
|
0.724
|
C
|
|
subtype
|
AUC
|
sky92
|
gep70
|
n
|
quality
|
|
FGFR3
|
0.932
|
0.661
|
0.779
|
77
|
A
|
|
t(4;14)
|
0.918
|
0.670
|
0.745
|
105
|
A
|
|
del(1p)
|
0.890
|
0.614
|
0.616
|
60
|
B
|
|
amp(1q)
|
0.878
|
0.655
|
0.736
|
203
|
B
|
|
del(13)
|
0.843
|
0.674
|
0.737
|
190
|
B
|
|
agnostic
|
0.724
|
0.615
|
0.648
|
769
|
C
|
Quality models




50% survival probability PFS (months)
|
quality
|
extreme
|
high
|
low
|
|
A
|
20.0
|
20.8
|
45.2
|
|
B
|
14.2
|
23.6
|
45.2
|
|
C
|
11.3
|
23.9
|
41.3
|
|
|
50% survival probability PFS
|
n
|
|
quality
|
extreme
|
high
|
low
|
extreme
|
high
|
low
|
|
A
|
20.0
|
20.8
|
45.2
|
37
|
10
|
59
|
|
B
|
14.2
|
23.6
|
45.2
|
37
|
31
|
257
|
|
C
|
11.3
|
23.9
|
41.3
|
37
|
90
|
642
|
GSE19784
Scatter plots by subtype


GSE19784 Guan cors
|
method
|
correlation
|
|
mmSYGNAL
|
0.276
|
|
SKY92
|
0.537
|
|
GEP70
|
0.388
|
GSE19784 PFS cors
|
method
|
correlation
|
|
mmSYGNAL
|
-0.275
|
|
SKY92
|
-0.529
|
|
GEP70
|
-0.379
|
Full model: all subjects
Full model ROC (first plot) uses all subjects with SYGNAL using the
best quality model.


Med PFS 50% (months)
|
methods
|
extreme
|
high
|
low
|
|
SYGNAL
|
8.845
|
20.740
|
31.517
|
|
GEP70
|
NA
|
6.253
|
30.602
|
|
SKY92
|
NA
|
3.355
|
28.873
|
logrank FDR values
|
risk
|
mmSYGNAL
|
GEP70
|
SKY92
|
|
extreme
|
NA
|
NA
|
NA
|
|
high
|
0
|
0
|
0
|
t(4;14)
t(4;14) ROC curve only shows the risk prediction for subjects
exhibiting the t(4;14) subtype.


Med PFS 50% (months)
|
methods
|
extreme
|
high
|
low
|
|
SYGNAL
|
14.03
|
4.982
|
NA
|
|
GEP70
|
NA
|
7.930
|
30.093
|
|
SKY92
|
NA
|
7.930
|
30.093
|
logrank FDR values
|
risk
|
mmSYGNAL
|
GEP70
|
SKY92
|
|
extreme
|
NA
|
NA
|
NA
|
|
high
|
0
|
0
|
0
|
GSE24080
Scatter plots by subtype


GSE24080 Guan cors
|
method
|
correlation
|
|
mmSYGNAL
|
0.332
|
|
SKY92
|
0.335
|
|
GEP70
|
0.338
|
GSE24080 PFS cors
|
method
|
correlation
|
|
mmSYGNAL
|
-0.287
|
|
SKY92
|
-0.288
|
|
GEP70
|
-0.371
|
Compare Guan to survival clinical outcome
Risk stratification by genetic abnormality subtype counts
Risk stratification by genetic abnormality subtype was done by first
calculating the number of high risk subtypes (del(17p), 1q+, FGFR3,
WHSC1 and MAF) each subject showed. All subjects were then ranked by
number of subtypes (0 to 6). For each subtype count category, subjects
were randomly ordered.
Rank ordering within each subtype count category was based on SYGNAL
risk probability for the stratification that combined SYGNAL risk
probability and subtype stratification.

Cytogenetics: change risk distribution
IA12 cytogenetics
|
cyto count
|
total
|
high
|
low
|
|
0
|
456
|
35%
|
65%
|
|
>0
|
313
|
40%
|
60%
|
|
1
|
194
|
38%
|
62%
|
|
2
|
81
|
40%
|
60%
|
|
3
|
33
|
55%
|
45%
|
|
4
|
5
|
40%
|
60%
|

Sample sizes of number of mutations
|
mutations
|
counts
|
|
4
|
5
|
|
3
|
33
|
|
2
|
81
|
|
1
|
194
|
|
0
|
456
|
KM survival plots
Risk stratification by subtype abnormality counts
del(13) and MAF subtypes are not included in subtype abnormality
counts.

Table of log rank test for difference of survival curves for subjects
with 0 abnormalities vs those with 1 to 5 abnormalities.
log rank p-values
|
count
|
p
|
|
1
|
0.660
|
|
2
|
0.281
|
|
3
|
0.033
|
|
4
|
0.448
|
|
0 v 1+
|
0.170
|
50% survival probability PFS (months)
|
abnormalities
|
50% PFS
|
n
|
|
4
|
12.7
|
5
|
|
3
|
23.8
|
33
|
|
2
|
30.1
|
81
|
|
1
|
32.6
|
194
|
|
0
|
39.1
|
456
|
KM plots cyto vs mmSYGNAL


Full model: all subjects
Full model ROC (first plot) uses all subjects with SYGNAL using the
best quality model.


50% survival probability PFS (months)
|
methods
|
extreme
|
high
|
low
|
|
SYGNAL
|
12.064
|
28.653
|
74.149
|
|
GEP70
|
NA
|
20.842
|
74.149
|
|
SKY92
|
NA
|
22.333
|
74.589
|
logrank FDR values
|
risk
|
mmSYGNAL
|
GEP70
|
SKY92
|
|
extreme
|
NA
|
NA
|
NA
|
|
high
|
0
|
0
|
0
|
t(4;14)
t(4;14) ROC curve only shows the risk prediction for subjects
exhibiting the t(4;14) subtype.


50% survival probability PFS (months)
|
methods
|
extreme
|
high
|
low
|
|
SYGNAL
|
12.268
|
31.042
|
NA
|
|
GEP70
|
NA
|
16.063
|
NA
|
|
SKY92
|
NA
|
13.657
|
64.084
|
logrank FDR values
|
risk
|
mmSYGNAL
|
GEP70
|
SKY92
|
|
extreme
|
NA
|
NA
|
NA
|
|
high
|
0
|
0
|
0
|
Full plots
ROC
t(4;14)

KM
Highest quality model


highest quality model
|
|
IA12
|
GSE19784
|
GSE24080
|
|
methods
|
extreme
|
high
|
low
|
extreme
|
high
|
low
|
extreme
|
high
|
low
|
|
SYGNAL
|
18.4
|
27.4
|
39.9
|
8.85
|
20.70
|
31.5
|
12.1
|
28.7
|
74.1
|
|
GEP70
|
NA
|
20.0
|
40.5
|
NA
|
6.25
|
30.6
|
NA
|
20.8
|
74.1
|
|
SKY92
|
NA
|
15.8
|
39.1
|
NA
|
3.36
|
28.9
|
NA
|
22.3
|
74.6
|
|
|
IA12
|
GSE19784
|
GSE24080
|
|
methods
|
extreme
|
low
|
high
|
low
|
high
|
low
|
high
|
|
mmSYGNAL
|
628
|
68
|
73
|
233
|
49
|
474
|
85
|
|
GEP70
|
608
|
0
|
161
|
205
|
77
|
503
|
56
|
|
SKY92
|
673
|
0
|
96
|
278
|
4
|
547
|
12
|
t(4;14)

t(4;14)
|
|
IA12
|
GSE19784
|
GSE24080
|
|
methods
|
extreme
|
high
|
low
|
extreme
|
high
|
low
|
extreme
|
high
|
low
|
|
SYGNAL
|
20
|
22.1
|
45.2
|
14.03
|
4.982
|
NA
|
12.268
|
31.042
|
NA
|
|
GEP70
|
NA
|
13.1
|
29.6
|
NA
|
7.930
|
30.093
|
NA
|
16.063
|
NA
|
|
SKY92
|
NA
|
12.4
|
29.6
|
NA
|
7.930
|
30.093
|
NA
|
13.657
|
64.084
|
Summary: predicted risk class
|
risk
|
IA12
|
GSE19784
|
GSE24080
|
|
clinical
|
predicted
|
mmSYGNAL
|
GEP70
|
SKY92
|
mmSYGNAL
|
GEP70
|
SKY92
|
mmSYGNAL
|
GEP70
|
SKY92
|
|
extreme
|
extreme
|
17
|
0
|
0
|
4
|
0
|
0
|
8
|
0
|
0
|
|
extreme
|
high
|
8
|
29
|
23
|
8
|
12
|
8
|
5
|
15
|
18
|
|
extreme
|
low
|
46
|
42
|
48
|
28
|
28
|
32
|
30
|
28
|
25
|
|
high
|
extreme
|
33
|
0
|
0
|
7
|
0
|
0
|
9
|
0
|
0
|
|
high
|
high
|
26
|
65
|
33
|
21
|
9
|
3
|
28
|
35
|
40
|
|
high
|
low
|
156
|
150
|
182
|
94
|
113
|
119
|
75
|
77
|
72
|
|
low
|
extreme
|
18
|
0
|
0
|
0
|
0
|
0
|
4
|
0
|
0
|
|
low
|
high
|
39
|
67
|
40
|
9
|
1
|
0
|
31
|
27
|
41
|
|
low
|
low
|
426
|
416
|
443
|
111
|
119
|
120
|
369
|
377
|
363
|
|
method
|
IA12
|
GSE19784
|
GSE24080
|
|
mmSYGNAL
|
0
|
0
|
0
|
|
GEP70
|
0
|
0
|
0
|
|
SKY92
|
0
|
0
|
0
|
ROC mmSYGNAL

